POS0181 THE IMPACT OF AUTOANTIBODIES (RF AND ACPA) ON THE EFFICACY OF BIOLOGICAL DISEASE-MODIFYING ANTIRHEUMATIC DRUGS IN RHEUMATOID ARTHRITIS: META-ANALYSIS OF RANDOMIZED CONTROLLED TRIALS
Authors: K. Takase-Minegishi, S. Böhringer, J. Nam, Y. Kaneko, F. Behrens, S. Saevarsdottir, J. Detert, M. Leirisalo-Repo, D. Van der Heijde, R. B. M. Landewé, S. Ramiro, D. Van der Woude
Journal: Annals of the Rheumatic Diseases (2023)

<h3>Background</h3> The impact of autoantibodies on the efficacy of biological disease-modifying antirheumatic drugs (bDMARDs) in patients with rheumatoid arthritis (RA) is not yet clear. Despite the fact that this information has been collected by several randomized controlled trials (RCTs), efficacy data for seropositive and seronegative patients separately have generally not been published. <h3>Objectives</h3> To comprehensively investigate the efficacy of bDMARDs in patients with RA with RF/ACPA compared to patients without these autoantibodies. <h3>Methods</h3> Previous systematic literature reviews performed by EULAR RA management task forces were searched for relevant RCTs published before February 2016<sup>[1–3]</sup>. RCTs including both autoantibody-positive (≤80% of total population) and -negative RA patients were eligible. We contacted authors and/or sponsors of RCTs to report aggregate results from analyses of individual patient data on clinical efficacy outcomes stratified for the presence of autoantibodies (RF+ vs RF-, ACPA+ vs ACPA-). Per trial, relative risks (RR) or mean differences comparing two groups (RF+ vs RF-, ACPA+ vs ACPA-) were calculated for various outcomes (ACR 20/50/70, DAS28 remission, delta DAS28, delta HAQ and radiographic progression) at the timing of the primary endpoint for the bDMARD-arm and the non-bDMARD-arm separately. Subsequently, relative risk ratios (RRRs) were computed, as the ratio of RR of the bDMARD-arm and the RR from the non-bDMARD-treated arm, reflecting whether seropositivity preferentially affected treatment response to bDMARD therapy. A meta-analysis was conducted using a mixed-effect meta-regression in subgroups of patients according to baseline autoantibody status. <h3>Results</h3> Data from 28 eligible RCTs were analyzed and from 23 pooled: 6 including csDMARD-naïve patients, 14 including csDMARD-inadequate responders (csDMARD-IR) and 3 including tumor necrosis factor inhibitor (TNFi)-IR patients. In csDMARD-naïve and csDMARD-IR, seropositivity was not associated with a better response to bDMARDs: Pooled 6-month ACR20 RRRs were 1.02 (0.88-1.18) and 1.09 (0.90-1.32), respectively (Figure 1A and B). Other outcomes followed the same pattern, with no difference between the groups. In TNFi-IR patients, based on 3 trials, the 6-month ACR20 RRR was 2.28 (1.31-3.95) (Figure 1C), favouring efficacy in seropositive patients. Other outcomes showed a similar effect, although with large confidence intervals and several reflecting a non-significant difference between the groups (Table 1). <h3>Conclusion</h3> In csDMARD-naïve and csDMARD-IR patients, autoantibodies did not have an impact on the efficacy of bDMARDs in RA. In TNFi-IR patients, there is a possible higher efficacy of bDMARDs in the seropositive group, but the low number of trials, large confidence intervals and inconsistent results across outcomes ask for caution in the interpretation. Seronegative TNF-IR patients may have very heterogenous underlying pathophysiological mechanisms, with a lower probability of good treatment response. Overall, in less treatment-resistant patients, the presence of autoantibodies was not associated with the treatment effect of bDMARDs. <h3>References</h3> [1-3] Nam JL, et al. Ann Rheum Dis. 2017;76:1113-36, 2014;73:516, 2010;69:976. <h3>Acknowledgements</h3> This presentation is based on research using data from Pfizer Inc. and AbbVie Inc. that has been made available through Vivli, Inc. This study, carried out under YODA Project #2017-2381, used data obtained from the Yale University Open Data Access Project, which has an agreement with JANSSEN RESEARCH &amp; DEVELOPMENT, L.L.C. The datasets of Roche (CSDR Research Proposal 5808) generated and analyzed during this study are available in anonymized format upon reasonable request via the CSDR platform. <h3>Disclosure of Interests</h3> Kaoru Takase-Minegishi Speakers bureau: Daiichi Sankyo, Gilead, Mitsubishi Tanabe, Stefan Böhringer: None declared, Jacqueline Nam: None declared, Yuko Kaneko Speakers bureau: Chugai, Grant/research support from: Chugai, Frank Behrens Speakers bureau: AbbVie, Amgen, Biotest, Boehringer, Bristol Myers Squibb, Celgene, Chugai, Genzyme, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, Sandoz, Sanofi, UCB, Consultant of: Amgen, Biotest, Boehringer, Bristol Myers Squibb, Celgene, Chugai, Genzyme, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, Sandoz, Sanofi, UCB, Grant/research support from: AbbVie, Prophylix, Saedis Saevarsdottir Employee of: deCODE genetics, Jaqueline Detert: None declared, Marjatta Leirisalo-Repo: None declared, Désirée van der Heijde Consultant of: AbbVie, Bayer, BMS, Cyxone, Eisai, Galapagos, Gilead, Glaxo-Smith-Kline, Janssen, Novartis, Pfizer, UCB, Employee of: Imaging Rheumatology bv, Robert B.M. Landewé Speakers bureau: Abbott, Amgen, BMS, Merck, Pfizer, Schering-Plough, UCB Pharma, Consultant of: Abbott, Amgen, AstraZeneca, BMS, GSK, Merck, Novartis, Pfizer, Schering-Plough, UCB Pharma, Grant/research support from: Abbott, Amgen, Novartis, Pfizer, Schering-Plough, UCB Pharma, Sofia Ramiro Consultant of: AbbVie/Abbott, Eli Lilly, Novartis, Pfizer, Sanofi, UCB, Grant/research support from: AbbVie/Abbott, Galapagos, Merck/MSD, Novartis, Pfizer, UCB, Diane van der Woude Consultant of: Galapagos.